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A Study on Forecasting Models for Cruise Demand: Comparisons Between South Korea and Hong Kong
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | LIM WEI NEE | - |
| dc.date.accessioned | 2019-12-16T02:57:49Z | - |
| dc.date.available | 2019-12-16T02:57:49Z | - |
| dc.date.issued | 2018 | - |
| dc.identifier.uri | http://repository.kmou.ac.kr/handle/2014.oak/11736 | - |
| dc.identifier.uri | http://kmou.dcollection.net/common/orgView/200000105223 | - |
| dc.description.abstract | The cruise industry has emerged to be an important part of the tourism sector since there has been a large increase in the number of passengers worldwide. The purpose of this study is to forecast cruise tourism demand, as doing so can ensure better planning, efficient preparation at the destination port and act as a basis for the elaboration of future plans. In this study, forecasting methods such as Exponential Triple Smoothing (ETS), Autoregressive Integrated Moving Average (ARIMA) and Group Method of Data Handling (GMDH) are tested to estimate the cruise demand and the best forecasting model is suggested by comparing the forecast accuracy. The total number of foreign cruise passengers are used as the measure of cruise demand. The results show that GMDH outperforms ETS and ARIMA in terms of forecasting accuracy. | - |
| dc.description.tableofcontents | Chapter 1: Introduction ..................................................... 1 1.1. Motivations and Objectives of Research ................ 1 1.2. Scope of Study ....................................................... 4 Chapter 2: Overview of Cruise Industry ........................... 5 2.1. History of Cruise .................................................... 5 2.2. Cruise Market ........................................................ 7 2.3. Cruise Tourism in South Korea ............................. 12 2.3.1. Cruise Tourism in Busan ................................... 17 2.4. Cruise Tourism in Hong Kong ............................... 20 2.5. Literature Review ................................................ 24 Chapter 3: Forecasting Models ....................................... 27 3.1. Autoregressive Integrated Moving Average (ARIMA) ........................................................................ 27 3.2. Exponential Triple Smoothing (ETS) ..................... 29 3.3. Group Method of Data Handling (GMDH) ............ 31 Chapter 4: Data Collection and Analysis ......................... 35 4.1. The Data .............................................................. 35 4.2. Analysis of Time Series Features of the Data ....... 37 4.3. Accuracy Measurement of Model ........................ 41 4.4. Experiment Results and Generating Future Forecasts....................................................................... 42 Chapter 5: Conclusions and Future Study ....................... 51 References ....................................................................... 53 Acknowledgments ........................................................... 57 | - |
| dc.language | eng | - |
| dc.publisher | 한국해양대학교 | - |
| dc.rights | 한국해양대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | A Study on Forecasting Models for Cruise Demand: Comparisons Between South Korea and Hong Kong | - |
| dc.type | Dissertation | - |
| dc.date.awarded | 2018-08 | - |
| dc.contributor.department | 대학원 해운경영학과 | - |
| dc.description.degree | Master | - |
| dc.title.translated | A Study on Forecasting Models for Cruise Demand: Comparisons Between South Korea and Hong Kong | - |
| dc.identifier.holdings | 000000001979▲200000000563▲200000105223▲ | - |
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